Senior Backend Engineer – AI Voice & Speech

Fdetimes; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Deepgram is seeking an engineer to join our Applied AI team focused on solving tough voice AI problems for enterprise customers. You will design scalable backend systems, improve STT/TTS quality, and iterate on model adaptation for enterprise domains.

We value hands-on AI/ML work, experience evaluating AI systems, and strong collaboration across teams. The role involves rapid experimentation and integration with ML models, backend platforms, and client devices.

Qualifications

• 4+ years of hands-on experience building and maintaining production cloud infrastructure.
• Hands-on AI/ML experience beyond using LLMs—training, fine-tuning, or adapting models.
• Experience evaluating AI systems with metrics, scoring, or evaluation tooling.
• Strong problem-solving skills and ability to adapt in a fast-paced startup.
• Excellent communication and cross-team collaboration capabilities.

Responsibilities

• Design, develop, and maintain scalable, high-performance backend systems for the platform.
• Improve speech-to-text and text-to-speech quality across environments.
• Expand robust scoring and evaluation of agents.
• Fine-tune and adapt models for customer vocabularies and domains.
• Optimize AI pipeline for performance in challenging audio environments and scale to new domains.
• Run experiments to validate product impact of new functionality.
• Collaborate with ML, backend, and client-device teams for seamless integration.

Skills

Cloud infra expertise

Applied AI/ML

Model evaluation

Problem solving

Collaboration

Education

Bachelor's or Master's in CS/Engineering

Tools

Python

Kotlin

TypeScript

Job description

Deepgram is seeking an engineer to join our Applied AI team focused on solving tough voice AI problems for enterprise customers. You will design scalable backend systems, improve STT/TTS quality, and iterate on model adaptation for enterprise domains.

We value hands-on AI/ML work, experience evaluating AI systems, and strong collaboration across teams. The role involves rapid experimentation and integration with ML models, backend platforms, and client devices.